Evidence map›Paper›PMID 30140966›Full record

ArticleJournal of the history of biology2018

More than Moore's Mores: Computers, Genomics, and the Embrace of Innovation.

Joseph November

Erratum issuedAbstract readHistorical Article
PubMed Publisher
In one paragraph

Article in Journal of the history of biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Activity-Based Protein Profiling (ABPP) of Oxidoreductases.Chembiochem : a European journal of chemical biology · 2021
    Review
  6. The dark side of technological advances in analysis of microbial ecosystems.Journal of animal science and biotechnology · 2019
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Joseph NovemberDepartment of History, University of South Carolina, Columbia, SC, USA. november@sc.edu.ORCID http://orcid.org/0000-0002-7896-864X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The genomics community has frequently compared advances in sequencing to advances in microelectronics. Lately there have been many claims, including by the National Human Genome Research Institute (NHGRI), that genomics is outpacing developments in computing as measured by Moore's law - the notion that computers double in processing capability per dollar spent every 18-24 months. Celebrations of the "$1000 genome" and other speed-related sequencing milestones might be dismissed as a distraction from genomics' slowness in delivering clinical breakthroughs, but the fact that such celebrations have been persistently encouraged by the NHGRI reveals a great deal about the priorities and expectations of the American general public, the intended audience of the genomics-computing comparison. By delving into the history of speculative thinking about sequencing and computing, this article demonstrates just how much more receptive to high-risk/high-payoff ventures the NIH and the general public have become. The article also provides access to some of the roots and consequences of the association of "innovation talk" with genomics, and the means to look past that association to the less glamorous (but arguably much more important) contributions of the NHGRI to building the field of genomics.

Indexed as

ComputersGenomicsHistory, 20th CenturyHistory, 21st CenturyHuman Genome ProjectInventionsNational Human Genome Research Institute (U.S.)United States$1000 genomeCarlson CurveComputersGenomeGenomicsGordon MooreHigh-speedHuman Genome ProjectInnovationMaintenanceMicroelectronicsMicroprocessorsMoore's lawNational Human Genome Research InstituteNational Institutes of HealthNHGRINIHRobert LedleySequencingSpeed

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.